International Journal of Contemporary Hospitality Management ( IF 11.1 ) Pub Date : 2023-01-03 , DOI: 10.1108/ijchm-06-2022-0705 Mike Tsionas, A. George Assaf
Purpose
The purpose of this note is to describe the concept of regression trees (RTs) for hospitality data analysis.
Design/methodology/approach
RT is an effective non-parametric predicting modelling approach that would free researchers from the need to force a certain functional form. The method does not require normalization or scaling of data.
Findings
The authors illustrate how RTs can be used to find a model that would result in the best prediction.
Research limitations/implications
A common challenge facing hospitality researchers is to estimate a regression model with the correct specification. RTs can help researchers identify the best explanatory model for prediction.
Originality/value
This paper describes the concept of RTs for the modelling of hospitality data.
中文翻译:
用于酒店数据分析的回归树
目的
本说明的目的是描述用于酒店数据分析的回归树 (RT) 的概念。
设计/方法/途径
RT 是一种有效的非参数预测建模方法,可以使研究人员摆脱强制某种函数形式的需要。该方法不需要对数据进行归一化或缩放。
发现
作者说明了如何使用 RT 来找到能够产生最佳预测的模型。
研究局限性/影响
酒店研究人员面临的一个共同挑战是估计具有正确规范的回归模型。RT 可以帮助研究人员确定最佳的预测解释模型。
原创性/价值
本文描述了用于酒店数据建模的 RT 概念。